In the field of computational biology, phylogeny is used to recognize the existing similarity between various species as well as the evolution engine (force) that has enabled these species to show modifications as time goes by. The use of these phylogeny techniques with a focus on computer viruses has allowed the finding of similarities between different malware families. This study presents the implementation of a proof of concept through the application of a technique used in the bioinformatics field, as is the case of the Neighbor Joining algorithm designed for the analysis of a group of computer samples. The aim will be to detect the similarity between the gathered samples, considering the similarity between the libraries of the system that uses this kind of programs.    

jmgutier@ulima.edu.pe; hquintan@ulima.edu.com

In this research, we posit the importance of including Computer Science topics in undergraduate Information Systems courses. A review of the existing literature has mentioned the importance of learning some Computer Science topics for an Information Systems career. Unfortunately, we have not found a consensus that could push this initiative. There is a set of concepts that Information Systems students should acquire from Computer Science or at least have a solid background in these areas. Therefore, we propose a set of courses from Computer Science that, we believe, should be considered in an Information Systems education.

One challenge in miRNA–genes–diseases interaction studies is that it is challenging to find labeled data that indicate a positive or negative relationship between miRNA and genes. The use of one-class classification methods shows a promising path for validating them. We have applied two one-class classification methods, Isolation Forest and One-class SVM, to validate miRNAs interactions with the ERBB2 gene present in breast cancer scenarios using features extracted via sequence-binding. We found that the One-class SVM outperforms the Isolation Forest model, with values of sensitivity of 80.49% and a specificity of 86.49% showing results that are comparable to previous studies. Additionally, we have demonstrated that the use of features extracted from a sequence-based approach (considering miRNA and gene sequence binding characteristics) and one-class models have proven to be a feasib...

The prediction of host human miRNA binding to the SARS-COV-2-CoV-2 RNA sequence is of particular interest. This biological process could lead to virus repression, serve as biomarkers for diagnosis, or as potential treatments for this disease. One source of concern is attempting to uncover the viral regions in which this binding could occur, as well as how these miRNAs binding could affect the SARS-COV-2 virus's processes. Using extracted sequence features from this base pairing, we predicted the relationships between miRNAs that interact with genes involved in immune function and bind to the SARS-COV-2 genome in their 5' UTR region. We compared two supervised models, SVM and Random Forest, with an unsupervised One-Class SVM. When the results of the confusion matrices were inspected, the results of the supervised models were misleading, resulting in a Type II error. However, with the latt...

In the current literature, there is limited evidence of the effects of teaching programming languages using two different paradigms concurrently. In this paper, we present our experience in using a multiparadigm and multiprogramming approach for an Introduction to Programming course. The multiparadigm element consisted of teaching the imperative and functional paradigms, while the multiprogramming element involved the Scheme and Python programming languages. For the multiparadigm part, the lectures were oriented to compare the similarities and differences between the functional and imperative approaches. For the multiprogramming part, we chose syntactically simple software tools that have a robust set of prebuilt functions and available libraries. After our experiments, we found that the students were strongly biased towards memorizing the syntax of these languages, jeopardizing their ab...

En el campo de la biología computacional se emplea la filogenia con el objetivo de reconocer la semejanza existente entre diversas especies, así como el motor de evolución que ha permitido que estas muestren modificaciones con el paso del tiempo. El empleo de estas técnicas de filogenia, orientadas hacia los virus computacionales, ha demostrado ser una alternativa que permite encontrar similitudes entre diversas familias de malware. En el presente trabajo se presenta la implementación de una prueba de concepto, mediante la aplicación de una técnica utilizada en el campo de la bioinformática, como es el caso del algoritmo de Neighbor-Joining, dirigido al análisis de un grupo de muestras de virus de computadoras. La finalidad será la detección de semejanzas entre las muestras recopiladas, tomando en consideración la similitud entre las llamadas “librerías del sistema” que ...

Steganography is the art or science of hiding information into a carrier in such a way that the hidden data could not be detected at first sight. Steganography techniques have broadened their scope of action, from hiding information into picture media, to audio steganography and to the field of network steganography. All these methods entail a potential threat to the information security policies of any business; having into the data leakage threats its likely focus. In this scenario, business corporations cannot remain blind to these types of threats and should consider adequate policies and prevention techniques to avoid these risks. We have analyzed in this article the potential dangers that an organization could face in the light of these types of steganography techniques along with a review of current commercial software vendors to analyze their offers and mishaps on Data Leakage Pr...

The task of elaborating accurate test suites for program testing can be an extensive computational work. Mutation testing is not immune to the problem of being a computational and time-consuming task so that it has found relief in the use of heuristic techniques. The use of Genetic Algorithms in mutation testing has proved to be useful for probing test suites, but it has mainly been enclosed only in the field of imperative programming paradigms. Therefore, we decided to test the feasibility of using Genetic Algorithms for performing mutation testing in functional programming environments. We tested our proposal by making a graph representations of four different functional programs and applied a Genetic Algorithm to generate a population of mutant programs. We found that it is possible to obtain a set of mutants that could find flaws in test suites in functional programming languages. Ad...

In the field of computational biology, phylogeny is used to recognize the existing similarity between various species as well as the evolution engine (force) that has enabled these species to show modifications as time goes by. The use of these phylogeny techniques with a focus on computer viruses has allowed the finding of similarities between different malware families. This study presents the implementation of a proof of concept through the application of a technique used in the bioinformatics field, as is the case of the Neighbor Joining algorithm designed for the analysis of a group of computer samples. The aim will be to detect the similarity between the gathered samples, considering the similarity between the libraries of the system that uses this kind of programs.    

This work seeks to show the situation of an undergraduate career related to information technologies and the low population of women among its students; in contrast to the great job opportunities and social mobility offered by this career, both locally and internationally. Indeed, today’s companies require professionals of careers linked to information technologies, and, moreover, seek diversity among their collaborators. This paper also aims to create a conceptual framework related to a marketing strategy and a methodology for the elaboration of a strategic marketing plan in order to increase the number of women in these careers. And also, to contribute to the gender balance in information technologies careers in Peru.

Cardiovascular diseases and Coronary Artery Disease (CAD) are the leading causes of mortality among people of different ages and conditions. The use of different and not so invasive biomarkers to detect these types of diseases joined with Machine Learning techniques seems promising for early detection of these illnesses. In the present work, we have used the Sani Z-Alizadeh dataset, which comprises a set of different medical features extracted with not invasive methods and used with different machine learning models. The comparisons performed showed that the best results were using a complete set and a subset of features as input for the Random Forest and XGBoost algorithms. Considering the results obtained, we believe that using a complete set of features gives insights that the features should also be analyzed by considering the medical advances and findings of how these markers influe...

This work is based on the results of the research “Analysis of the use of software quality models: a proposal to improve processes in the ‘mypes’ producing software in Lima”, which was supported by the Institute of Scientific Research of the University of Lima. The study characterized “mypes” and showed that they do not have an adequate use of software quality models, both in their processes and products. In addition, these companies recognized that they have problems in their processes and the need to improve them. It was therefore proposed to develop a further research setting a suitable and sustainable process improvement model for each category of “mype”, based on an in-depth analysis of existing quality models, that could be applied throughout the entire software lifecycle: from the establishment of requirements to the quality tests.

This work seeks to show the situation of an undergraduate career related to information technologies and the low population of women among its students; in contrast to the great job opportunities and social mobility offered by this career, both locally and internationally. Indeed, today’s companies require professionals of careers linked to information technologies, and, moreover, seek diversity among their collaborators. This paper also aims to create a conceptual framework related to a marketing strategy and a methodology for the elaboration of a strategic marketing plan in order to increase the number of women in these careers. And also, to contribute to the gender balance in information technologies careers in Peru.

Nowadays, the increasing amount of information provided by hyperspectral sensors requires optimal solutions to ease the subsequent analysis of the produced data. A common issue in this matter relates to the hyperspectral data representation for classification tasks. Existing approaches address the data representation problem by performing a dimensionality reduction over the original data. However, mining complementary features that reduce the redundancy from the multiple levels of hyperspectral images remains challenging. Thus, exploiting the representation power of neural networks based techniques becomes an attractive alternative in this matter. In this work, we propose a novel dimensionality reduction implementation for hyperspectral imaging based on autoencoders, ensuring the orthogonality among features to reduce the redundancy in hyperspectral data. The experiments conducted on the...

Crime continues to be an issue, in Metropolitan Lima, Peru affecting society. Our focus is on property crimes. We recognized the lack of studies on predicting these crimes. To tackle this problem, we used regression techniques such as XGBoost, Extra Tree, Support Vector, Bagging, Random Forest and AdaBoost. Through GridsearchCV we optimized hyperparameters to enhance our research findings. The results showed that Extra Tree Regression stood out as the model with an R2 value of 0.79. Additionally, error metrics like MSE (185.43) RMSE (13.62) and MAE (10.47) were considered to evaluate the model's performance. Our approach considers time patterns in crime incidents. Contributes, to addressing the issue of insecurity in a meaningful way.